Traditionally, electrical power usage was measured by a centralized power meter attached to a building. Independent of whether the building was a home, commercial office, or factory, the power usage was measured by a single device that could be read at regular intervals to determine the total power consumption of the facility over a given period. Under this approach, the ability to determine power consumption by time of day or for specific equipment was extremely limited and essentially required some type of continuous monitoring of the power meter correlated to events in the facility.
More recently, a general societal trend towards increased power consumption efficiency, along with corresponding governmental policies and regulations, has driven demand for increased ability to monitor detailed power consumption. Additionally, power suppliers are implementing procedures and billing practices designed to incentivize power efficiency and stabilize the power grid. For example, power suppliers may install meters on buildings that record power usage at fifteen minute intervals. The power supplier can then use this information to charge the building owner a fee based on the building's peak demand in addition to the overall consumption. This additional fee encourages building owners across the grid to reduce their peak demand in order to achieve direct savings and thus increases the power available on the grid during peak hours.
One method to prevent power grid failures that has recently been implemented is called a demand response system. In the demand response system, when a utility provider recognizes that peak load will exceed capacity (or allowable limits), the utility provider can contact one or more building operators and instruct the operators to remove their loads from the power grid. This contact can also be implemented by sending a demand response signal to the buildings. In response, the individual building operators provide the power to their buildings using alternative means (such as a generator) and thus remove their loads from the grid. These arrangements are typically negotiated in advance, and provide penalties to building operators who do not remove their loads. Additionally, current demand response systems are binary in nature; either the buildings loads are on the grid or they are off the grid.
Intelligent metering is another emerging conservation method designed to allow companies to monitor their power consumption based on several parameters such as the time of day, types/amount of equipment operating, occupancy level of the building, etc. Through the use of intelligent metering, companies can identify policies, procedures, and operational practices that are costing the company unnecessary money through increased power consumption and take steps to eliminate these costs. Additionally, as regulatory policies place increased demand on companies for efficiency of power consumption, many companies will need to implement intelligent monitoring in order to meet such regulations. Through intelligent metering companies can also detect faulty equipment that is wasting power and easily identify and fix the problem before significant costs are incurred by increased power consumption.
Although an advancement from prior techniques, intelligent metering still relies upon significant operator involvement in order to realize any power savings. For example, intelligent metering may identify that a company's power consumption increases 25% at a certain time of day during which the company is charged a premium rate due to increased grid-wide demand. Although this information is useful to know, it does not result in any increased efficiency until the company performs an analysis of the causes of the increased load and designs policies to reduce the load. In other words, current practices rely on analyzing historical data, predicting future power consumption, and then implementing policies in order to reduce the future power consumption. As a result, current practices are not flexible enough to provide real-time power consumption control or, in other words, do not allow for proactive control strategies.
Moreover, current implementations of power consumption management rely upon switching loads on or off and/or time shifting to manage power usage. Specifically, if a building is using too much power during peak hours, the only option to reduce consumption is to switch some loads off or move the operation of those loads to other hours of the day. For example, the thermostat for a building may be turned up several degrees so that the fans and compressors of the Heating, Ventilation, and Air Conditioning (HVAC) system run less frequently. As another example, major power-consuming pieces of equipment may be idled during peak hours and scheduled to run after hours instead. All of these measures result in some perceptible change to the environment or operating procedures of occupants in the building. Occupants may, for example, perceive that their work environment is hotter as the thermostat is increased and their productivity may decrease as their bodies respond to the hotter environment. Thus, current on/off solutions may sacrifice productivity for power savings.
One area that is noticeably neglected in existing power consumption management solutions is interior lighting. Interior lighting can represent a significant amount of the total power demand in a building at any given time and may be as much as 70% of the total power demand, depending on the type of building. However, simply turning off the lights in a building is generally not an acceptable solution to decreasing power demand because the occupants of the building will require lighting in order to perform their job functions. Consequently, current power consumption management solutions are ill-suited to reduce the power consumed by interior lighting in order to reduce total power demand.